We analyze the effectiveness of different pre-training settings through ablation studies over the 7 downstream tasks.
In addition to the above mentioned standard metrics, we also compute the Meta Average score (average of the results across all tasks) as a global metric.
The complete ablation study is listed in Table. REF .
In these experiments, we use a ResNet50-based 6-layer CommerceMM, i.e., the number of layers of text encoder and multimodal fusion together equals 6, initialized from XLM-R-small [1]}.
All models are trained in an end-to-end manner.
